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[英]Pandas applying slice_replace with for loop and conditional statement
[英]Pandas slice_replace with series
當前slice_replace
方法不接受pd.Series
作為repl
參數:
MWE:
# Example as in the doc
pd.Series(['azerty_0', 'azerty_1']).str.slice_replace(1, 3, repl='repl')
Out[28]:
0 areplrty_0
1 areplrty_1
dtype: object
# Passing a pd.Series does all combinations
pd.Series(['azerty_0', 'azerty_1']).str.slice_replace(1, 3, repl=pd.Series(['repl_0', 'repl_1']))
Out[29]:
0 0 arepl_0rty_0
1 arepl_1rty_0
dtype: object
1 0 arepl_0rty_1
1 arepl_1rty_1
dtype: object
dtype: object
# Expected result
pd.Series(['azerty_0', 'azerty_1']).str.slice(0, 1) + pd.Series(['repl_0', 'repl_1']) + pd.Series(['azerty_0', 'azerty_1']).str.slice(3)
Out[30]:
0 arepl_0rty_0
1 arepl_1rty_1
dtype: object
有沒有更好的方法來實現這個結果?
找不到任何更好的替代方案,您可以使用它代替切片功能的一個是在 str 上進行列表切片,即
s = pd.Series(['azerty_0', 'azerty_1'])
rep = pd.Series(['repl_0', 'repl_1'])
new = s.str[:1]+ rep +s.str[3:]
另一個班輪是:
new = s.str.partition('ze').rename(columns={1:'x'}).assign(x=rep).sum(1)
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